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A Comparative Analysis of Content Delivery Capability for Collaborative Dual-Architecture Network

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Abstract

In order to deliver Internet content to people of the world for achieving the vision of “The Internet is for everyone”, our group pioneered a collaborative dual-architecture network (DAN). For quantitative analysis of DAN’s content delivery capability, in this paper we firstly propose a unified comparative model, in which network performance and user utility are taken into account. Then, by applying the model we conduct direct and indirect comparative analysis in detail. Numerical results shed light on that DAN outperforms TCP/IP, NDN (named data networking) and BSN (broadcast-storage network) in terms of delivery capability. Given this, we argue that DAN is favourable for content delivery.

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Acknowledgment

We would like to express our heartfelt gratitude to Prof. Youping Li and the reviewers for their insightful suggestions. This work is supported by National Science Foundation of China under grants No. 61672155, No. 61472080, No. 61272532, Consulting Project of Chinese Academy of Engineering under grant No. 2018-XY-07, National High Technology Research and Development Program of China under grant No. 2013AA013503, and Collaborative Innovation Center of Novel Software Technology and Industrialization.

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Correspondence to Peng Yang .

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© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Liu, X., Yang, P., Dong, Y., Ahmed, S.H. (2018). A Comparative Analysis of Content Delivery Capability for Collaborative Dual-Architecture Network. In: Romdhani, I., Shu, L., Takahiro, H., Zhou, Z., Gordon, T., Zeng, D. (eds) Collaborative Computing: Networking, Applications and Worksharing. CollaborateCom 2017. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 252. Springer, Cham. https://doi.org/10.1007/978-3-030-00916-8_7

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  • DOI: https://doi.org/10.1007/978-3-030-00916-8_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-00915-1

  • Online ISBN: 978-3-030-00916-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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